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Predictive analytics early adopters focus on individual customer analysis

Early adopters are tapping predictive analytics to foretell customer behavior at the individual level to reduce churn and identify up-sell opportunities.

ALEXANDRIA, Va. – Target isn’t just a name for the Minneapolis-based retail chain. The company applies that term to business operations on a daily basis, using predictive analytics technology to target its marketing programs to individual “guests,” as Target calls its customers.

“We are able to derive guest expectations through mining our data,” said Andrew Pole, head of media and database marketing at Target.

Target isn’t the only company that uses predictive analytics to zero in on customer behavior and expectations on a micro level. In fact, rather than identifying and predicting larger market or economic trends, most early adopters of the technology are using predictive analytics software to tailor marketing campaigns and identify up-sell opportunities down to the individual customer level, according to speakers at the Predictive Analytics World conference here. The goal, they said, is to better understand what specific customers are likely to spend their money on.

Take Paychex Inc. The Rochester, N.Y.-based company’s core business is processing payrolls for its corporate clients. Paychex also offers 401(k) services, a business it is eager to expand. Until recently, however, Paychex sales reps were cold calling payroll clients to see if they might be interested in adding the 401(k) services, according to Jason Fox, an information system and portfolio manager in Paychex’s enterprise risk management division.

The cold calling proved to be an inefficient way to sign up new 401(k) customers: Nearly half of Paychex’s clients use the company’s payroll services but not its 401(k) offerings. “That’s a lot of revenue to leave on the table,” Fox said.

Predictive analytics tools point the way to prospective customers
The company decided to invest in predictive analytics technology to help identify which of its payroll-only clients were the most likely to be interested in its 401(k) business. The analytics routines take into account whether a client uses a competitor’s 401(k) services or none at all, as well as its credit rating and payment history at Paychex.

With the most likely 401(k) clients identified, Paychex can then allocate its available marketing budget to the various prospects based on their perceived value and likelihood of signing on, Fox said.

At Monster Worldwide Inc., Jean Paul Isson and his team are using predictive analytics technology to help differentiate the New York-based company from other online careers sites.

In addition to its flagship job posting services, Monster offers services such as resume mining and careers website hosting to corporate clients. Predictive analytics helps Monster identify which services to market to which clients, said Isson, who is vice president of the company’s global business intelligence and predictive analytics division.

Isson added that the predictive analytics software has become a crucial tool for the company as it takes on new, and free, job listing sites in the careers services market. “It’s the only way we can optimize ourselves,” he said.

Using predictive analytics to keep the cash registers ringing
At Target, predictive analytics technology helps the retailer maximize the amount of revenue it gets from each customer, whether people shop online or in stores, while also enabling the company to allocate its marketing resources more efficiently, Pole said.

With data mined from online transactions, loyalty card use and demographics databases, for example, Target creates a profile of each customer and determines the amount of money that he or she is likely to spend with the company in a given year.

So if, with the help of the predictive analytics software, Target determines that customer X can afford to spend $5,000 annually, the company tailors its marketing efforts accordingly. And when the customer reaches the $5,000 mark, Target can stop spending money marketing to him if it decides that any additional efforts aren’t likely to induce him to make more purchases, Pole said.

Target also uses predictive analytics to determine how much of a marketing investment is required to get a particular customer to buy a certain product. For some customers, a $1 coupon might be enough to get them to buy dishwasher soap, while others might need only half of that to induce a sale. With that kind of information in hand, Pole said, Target’s marketing department can decide which customers are worth marketing to in given situations.

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